Real-time data provides more accurate branch staff schedules
For all the changes in branch operations over recent decades, the fundamentals for delivering on service standards remain firm. Account holders expect friendly professional service and accurate transactions—and they don’t want to wait around for either.
While those expectations hold firm, the methods that financial institutions can employ to deliver great service as efficiently as possible have improved dramatically, especially in the area of staff scheduling. Time studies, a once-commonplace method for measuring employee output, have largely been replaced by systems that rely on real-time data on staffing and branch volume.
Time study refers to a structured process of directly observing and measuring employees’ work, literally counting the minutes to establish the average time required to complete specific tasks when working at a defined level of performance. In the past, time studies might have been a useful tool in scheduling staff in combination with forecasts of expected traffic. But in today’s fast-paced environment, relying on a manual process tied to forecasts based on historical patterns may lower service levels and increase costs.
You might say that the use of time studies in branch scheduling is well past its expiration date.
Financial institutions now have the opportunity to apply real-time data to guide scheduling, with much more accurate information about assist times, or the amount of time frontline employees typically spend with account holders to complete specific tasks. Rather than a general estimate of assist times across a wide range of product and service requests, lobby tracker software captures the actual time it takes to process individual interactions.
This data-based system can supply a whole host of information that would be impossible (or at least prohibitively expensive) to collect through time studies or is outside the purview of that tool, including assist times per product for individual employees; patterns in branch traffic and transactions by time of day, week, or month; and new accounts opened and other relevant sales statistics.
An automated alternative to the time study can facilitate more efficient staff scheduling and even alert managers when unexpected traffic spikes extend wait times beyond the financial institution’s specified target. In that event, other employees can step in to assist when needed to maintain service levels.
Compare that functionality to the practice of calculating staffing needs manually and based on historical patterns. If time studies are “close,” they might be just a minute off here and there—which is still significant when multiplied by the rate of transactions that occur over the course of a week or month. And that approach can’t account for differing traffic patterns and assist times from branch to branch, which widens the accuracy gap even more. However slight, those variations can add up to significant costs over time in terms of poor service and/or overstaffing.
The disparities between time-study estimates and real-time data can build up to the point that branch managers either abandon the use of that information in scheduling or continue to rely on inexact figures. Either way, staff schedules are not aligned with current traffic patterns, and the financial institution ends up either short-staffed or overstaffed.
The use of real-time data ensures that the basis for scheduling is continually updated and remains as accurate as possible going forward. In comparison, time studies are past their “sell-by date” soon after they are completed.
Access to real-time data in scheduling is especially crucial in state-of-the-art branches staffed with universal employees. Account holders are likely to use these service centers differently than when they relied on traditional branches, especially if the financial institution’s strategic aim is to encourage a new sales and service model in these settings. Over time, branch visits may take longer and result in higher sales as account holders shift away from routine transactions and toward more consultative interactions.
Universal employees tend to earn more than traditional tellers, so appropriate staffing becomes even more important to the bottom line. A lobby tracker system collecting real-time data keeps pace with evolving traffic patterns and customer expectations in a way that no time study can.
There was an era when time studies were considered a top-shelf solution for aligning staff schedules with the best possible estimates of service needs. But that approach is now out of date. The time that matters most to account holders is when they walk into a branch—and only real-time data can keep pace with those expectations.